This paper introduces the structural threshold regression model that allows for an endogeneous threshold variable as well as for endogenous regressors. This model provides a parsimonious way of modeling nonlinearities and has many potential applications in economics and .finance. Our framework...

This paper introduces the structural threshold regression model that allows for an endogeneous threshold variable as well as for endogenous regressors. This model provides a parsimonious way of modeling nonlinearities and has many potential applications in economics and finance. Our framework...

This paper provides empirical support for one theory of transition delays: initial land inequality. Using a new historical data set for land inequality (Frankema (2009)) we employ duration analysis to investigate whether higher levels of land inequality lead to longer delays in the extension of...

In this paper, we investigate the relationship between foreign aid and growth using recently developed sample splitting methods that allow us to uncover evidence for the existence of heterogeneity and nonlinearity simultaneously. We also implement a new methodology that allows us to deal with...

We uncover evidence of substantial heterogeneity in the growth experience of countries using a structural threshold regression methodology. Our findings suggest that studies that seek to promote mono-causal explanations in the institutions versus geography debate in growth are potentially misleading

We uncover evidence of substantial heterogeneity in the growth experience of countries using a structural threshold regression methodology. Our findings suggest that studies that seek to promote mono-causal explanations in the institutions versus geography debate in growth are potentially...

This paper extends the simple threshold regression framework of Hansen (2000) and Caner and Hansen (2004) to allow for endogeneity of the threshold variable. We develop a concentrated least squares estimator of the threshold parameter based on an inverse Mills ratio bias correction. We show that...